A digital phased array includes a plurality of antennas formed into an array. The phased array works by forming abeam with an array of antenna elements in a certain direction, thus causing a high gain relative to a signal of interest. The signal of interest could be a desired signal originating from a target for which tracking using the phased array is desired or an interference signal. In some cases, the interference signal may be intentionally provided in the form of a jamming signal. Thus, one challenge associated with operation of a digital phased array is to accurately preserve a signal coming from a target, white minimizing the effects of interfering signals coming from other directions.
Conventional digital phased arrays may employ a signal processor to facilitate cancellation of interference signals. Two relatively well known solutions for interference cancellation include a Side-Lobe Canceller (SLC) and the Linearly Constrained Minimum Variance (LCMV) beamformer. SLC employs a low gain auxiliary channel with a near uniform gain pattern over the steerable range of the main beam. With this configuration, any interference in the side lobe of the main beam can be subtracted out of the desirable signal in the main beam using the information in the auxiliary channel. Of course, the signal of interest wilt also be present in the auxiliary channel and some signal loss will occur when subtracting from the main beam. However, the loss is generally expected to be relatively small because the gain in the main beam is much larger than the gain of the auxiliary channel.
In contrast to SLC, LCMV beamformer is a method for calculating the beamforming weights of an array. In conventional beamforming, the typical weights are just those that will introduce a progressive time delay to each unit such that the array is steered in a certain direction. LCMV adaptively computes weights that will steer the array in the desired direction, but also have nulls in the directions of interference while minimizing main beam losses. Thus, LCMV achieves the same objective as SLC with respect to interference removal. However, LCMV also minimizes loss to the signal of interest.
Both SLC and LCMV were introduced decades ago. However, SLC has remained the dominant algorithm employed in large systems having hundreds of elements due to the computational cost associated with LCMV. While SLC may be more practical for implementation, SLC does not necessarily perform as well as LCMV due to the fact that SLC causes signal loss and has difficulty performing for main-beam interference. Computing hardware is much more mature today, and thus it may be more practical to implement LCMV than it had been in the past. However, LCMV still presents significant computational challenges for signals with a wide bandwidth and when the array has a large number of elements. Thus, it may be desirable to develop an algorithm that can perform interference cancellation while avoiding some of the performance degradations described above.